The marketing ecosystem is about to undergo a radical upheaval. We are swimming in a sea of data, but access to this data is becoming increasingly restricted.
The old ways of accessing the public—cookies, third-party identifiers—are crumbling before our eyes. We can’t avoid the inconvenient truth: Due to global and local macroeconomic forces impacting media and digital, nearly the entire open internet will soon become untraceable.
We need to change the way we think about data and technology to thrive in the next era of media, and the answer lies in embracing the transformative power of predictive technology.
I believe predictive technology will have a major impact in three key areas: predictive planning, where it will help brands move beyond the limitations of 1:1 targeting; predictive optimization, where AI will unlock campaign success; and predictive content, where dynamic, personalized experiences will transform audience connection.
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Predictive Planning: Moving Beyond the Limits of 1:1 Targeting
For years, marketers have chased the holy grail of 1:1 precision targeting. But with growing privacy concerns and walled gardens casting long shadows, that approach is proving untenable.
Instead of focusing on individual data points, we need to expand our data aperture and move from siloed audience planning to unified multi-channel, multi-platform planning.
The only way to achieve unified audience planning is to create a new common currency for identity, leveraging the power of hyperlocal data for improved targeting. Hyperlocal data strikes the right balance between scale and precision.
It’s a tapestry woven from location data, demographic data, psychographic data, and even purchasing behaviors. By analyzing these threads together, we gain a nuanced understanding of consumer behavior in specific geographies.
This allows us to reach entire communities that are ready to receive the message. Imagine, for example, a healthy burger campaign that targets neighborhoods with high concentrations of fast food and health food stores. What if we could enrich those areas with the most transactional customer cohorts for health equipment purchases, gym memberships, and fast food purchases? That’s the power of hyperlocal data in action.
Predictive Optimization: Harnessing the Power of AI for Campaign Success
The volume of data available today is overwhelming, even for the most seasoned marketers. We also know that in today’s environment, brands need to do more with less. That’s where AI comes in, acting as a tireless assistant capable of uncovering insights and optimizing at a rapid pace.
AI in media is not new, but it is accelerating. Already, about 69% of all advertising is touched by AI in some way, andGroupM plans to reach 94% globally by 2029.
AI-powered predictive optimization can help deliver the performance optimization brands are looking for by analyzing large data sets to identify patterns and trends, allowing marketers to refine campaigns in real-time. Programmatically, there are a multitude of data points and endless optimization possibilities.
We can enable in-flight optimization and automatically adjust bidding strategies based on real-time signals (weather, pollen counts, sports scores), on-site behavior, and product availability. Imagine an airline that only optimizes available flight routes based on real-time seat availability.
Providing algorithms tailored to custom goals with an automated model prioritization approach to optimize for high-margin products can far outperform a standard CPA (cost per action) model, which is a blunt instrument for brands.
AI will bring real value in the future by helping us optimize campaign spend across channels with consistent audience approaches across DOOH, addressable TV, digital, and audio, enabling us to improve targeting effectiveness and return on ad spend (ROAS). This level of granular control allows marketers to maximize ROI and ensure every dollar spent generates tangible results.
The balance is to equip our teams with tools that allow us to leverage human ingenuity powered by machine learning to deliver maximum performance optimization and thus maximize media investments. Predictive optimization can also reveal detailed insights that can inform a predictive content strategy.
Ryan Menezes
Predictive content: Ffrom static ads to dynamic, personalized experiences
In a content-saturated world, capturing and retaining audience attention is more challenging than ever. The key is being able to deliver personalized experiences that resonate at the individual level, at scale. That’s where predictive content comes in.
By leveraging artificial intelligence and machine learning, we can analyze consumer data to predict what type of content is most likely to resonate with specific audiences. This could mean tailoring ad copy to reflect local slang or dynamically generating video ads featuring products that are relevant to a user’s browsing history or propensity to purchase. This shift from static ads to dynamic, personalized stories allows brands to build deeper connections and deliver truly memorable experiences.
These three pillars of predictive technology will transform brands in the near future. By embracing hyperlocal data, AI-driven optimization, and dynamic content creation, we can navigate the ever-changing media landscape and build meaningful connections with audiences.
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